paulecoffet / birdsonglearningmodel Goto Github PK

The pitch found by the current algorithm is way to high. The YIN pitch is also too unstable to be fit perfectly.

The branch pitch_prio will try to improve this pitch fit, by changing both the priority measures and the prior. This branch is only for a better fit and is not bound to any hypothesis.

Even if optimisation during the day is suppose to only increase the song mimicry performance, it sometimes has a huge negative impact. Optimizing locally seems to sometimes yield overall decrease in performance.

Training a gesture in context of its surrounding gesture was suppose to minimise this effect. It worked but the issue is still present.

In the current generated song, the Wiener Entropy is way too low. This seems to be due to too slow oscillation in the parameters. New priors exploration in the branch entropy_fit will investigate this issue.

The hypothesis:

• Allow faster oscillations and put a prior of one fast oscillation for amplitude will increase wiener entropy.

Expected results:

• More complex sounds with more entropy, without deterioring the amplitude measure.